Made in Humane Club
A/B Testing
You’re standing before an ice cream shop. They’ve got two new, irresistible flavors—Monsoon Mango or Jackfruit. So… which one do you choose? It’s a TOUGH call. But what if you could… taste both before deciding? In business, that is called A/B Testing. It lets you sample the options before doubling down on the winner.
In A/B testing, you split your audience into two groups—Group A and Group B. Group A sees the experiment. Group B doesn’t. Then… you compare which group does better. And just like that—you have your winner.
Why A/B Testing MATTERS
Business is all about continuous learning. And to learn… you need fresh information. But here’s the kicker: You can’t rely on assumptions. Because assumptions deceive. Guesses? They mislead. What you THINK works… often doesn’t. What seems minor… sometimes, it’s MAJOR.
A/B testing removes the guesswork from decisions. Amazon. Netflix. Google. They ALL know this. That’s why they test—constantly. Because every tweak… every change… every experiment… compounds the growth.
Power Analysis
How do you know if your test results are legit? Well… the bigger the sample, the more reliable the signal. But how big is “big enough”? That’s where Power Analysis steps in! Power Analysis helps you figure out how many observations you need to spot a meaningful change.
But here’s the twist: The more subtle the change you are looking to detect… the MORE observations you need. More time. More patience.
Want to detect a tiny 5% change with 95% confidence? Buckle up. You’ll need 10,000 observations. That’s 5,000 per group.
If you don’t have that many, then you’ve got two choices:
- Hunt for bigger changes (like 20% instead of 5%)
- Or… compromise and lower your confidence (80% instead of 95%)
But can you compromise? That depends on how much risk can you carry? And how subtle a change do you NEED to detect? For example, in pharmaceutical trials, a tiny 5% side-effect increase can mean… life or death…. whereas in website redesigns, aim for 20% improvement. Go big.
Because in testing—as in life—it all boils down to this: Know what you’re chasing and know what you’re willing to sacrifice.
CopiedThe Multi-Armed Bandit
Now… what if you need to test MORE than just A and B? What if you’ve got, say… FOUR options? That’s when the Multi-Armed Bandit takes the stage.
Here’s how it plays out:
- It tests all the four contenders on JUST 20% of your audience.
- Once it finds the TOP contender, that winner gets served to the remaining 80% of your audience.
The result? Maximum gains. Minimal waste. And the testing? It never stops. The Bandit just keeps searching for… something even better.
CopiedTraps to Avoid
A/B Testing, like any tool, can mislead if not used carefully. Watch out for these pitfalls:
- Beware of small samples. If you’ve too few observations then your results might just be noise.
- Always define what you’re testing—and the expected outcome.
- Don’t test multiple things on the SAME group. Crossed signals will sabotage your results.
Plan ahead. Stay sharp. Or risk testing that teaches you nothing.
Running Multiple Tests Simultaneously
Thinking of running multiple tests at once? You can! BUT… only if:
- The test groups are distinct. For instance, one test targets logged-in users; another tests on logged-out ones.
- The features are independent. If one test tweaks the conversion funnel, the other should stay FAR away from it.
Final Thoughts
A/B Testing isn’t some dry, mechanical exercise. It’s… exploration. Discovery. Learning. Because A/B Testing isn’t just about learning what works—it’s about understanding WHY it works. So, test BOLDLY. Test BRAVELY. And when the data speaks—listen.